• Management & Information Systems Review
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• v.34 no.1
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• pp.179-190
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• 2015

Local governments are commercializing natural environment, one of tourist commodities, to ensure that the proceeds from sale of tourist commodities are returned to local residents(Han Yeong-joo, Lee Moo-yong, 2001). In Songdo beach, Busan, cable car dismantled in 1980s due to the run-down state of the facility is poised for restoration in 26 years and can be said to be of great value as tourist commodity of the region and necessitates the demand forecast. To overcome limitations of demand forecast in existing studies, the analysis was made based on feasibility rate(Gruber index, self-confidence index), the realizable predictive value, for the willingness-to-visit rate when forecasting the demand of visitors. The results of demand forecast suggested that number of visitors would range from approximately 550,684 persons to 1,514,416 persons when the target region for demand forecast was confined to Busan Metropolitan City, and was in the range between 1,013,740 persons and 2,854,340 persons when the target region was expanded to cover Busan, Ulsan, and Gyeongnam. Based on the results of this study, estimation of visitors and demand forecast for Songdo offshore cable car restoration which reflect characteristics of Songdo beach of Busan would provide important basis for proceeding with tourism industry development project.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.528-550
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• 2024

Warehousing demand prediction is an essential part of the supply chain, providing a fundamental basis for product manufacturing, replenishment, warehouse planning, etc. Existing forecasting methods cannot produce accurate forecasts since warehouse demand is affected by external factors such as holidays and seasons. Some aspects, such as consumer psychology and producer reputation, are challenging to quantify. The data can fluctuate widely or do not show obvious trend cycles. We introduce a new model for warehouse demand prediction called MAGRU, which stands for Multi-layer Attention with GRU. In the model, firstly, we perform the embedding operation on the input sequence to quantify the external influences; after that, we implement an encoder using GRU and the attention mechanism. The hidden state of GRU captures essential time series. In the decoder, we use attention again to select the key hidden states among all-time slices as the data to be fed into the GRU network. Experimental results show that this model has higher accuracy than RNN, LSTM, GRU, Prophet, XGboost, and DARNN. Using mean absolute error (MAE) and symmetric mean absolute percentage error(SMAPE) to evaluate the experimental results, MAGRU's MAE, RMSE, and SMAPE decreased by 7.65%, 10.03%, and 8.87% over GRU-LSTM, the current best model for solving this type of problem.

• Journal of the Korean Institute of Navigation
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• v.8 no.1
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• pp.1-16
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• 1984

The economical property of a shipping enterprise, as well as other transportation industries, is determined by the difference between the freight earned and expense paid. This study can be regarded as a division of optimizing ship allocation to routes under the integrated port transport system. Fleet planning and scheduling require complicated allocations of cargoes to ships and ships to routes in order to optimize the given criterion function for a given forecast period. This paper deals with the optimum ship allocation problem minimizing the operating cost of ships in a shipping company. Optimum fleet operating for a shipping enterprise is very important, since the marine transportation is a form of large quantity transport requiring long-term period, and there is a strong possibility to bring about large amount of loss in operation resulting from a faulty ship allocation. Where there are more than one loading and discharging ports, and a variety of ship's ability in speed, capacity, operating cost etc., and when the amount of commodities to be transported between the ports has been determined, then the ship's schedule minimizing the operating cost while satisfying the transport demand within the predetermined period will be made up. First of all a formula of ship allocation problems will be established and then will be constructed to solve an example by the Integer Programming application after consideration of the ship's ability, supply and demand of commodity, amount of commodity to be transported, operating costs of each ship etc. This study will give good information on deciding intention for a ship oprator or owner to meet the computerization current with shiping management.